Search Results for author:
Found 3 papers, 2 papers with code
Structural Group Unfairness: Measurement and Mitigation by means of the Effective Resistance
We denote the social capital disparity among different groups in a network as structural group unfairness, and propose to mitigate it by means of a budgeted edge augmentation heuristic that systematically increases the social capital of the most disadvantaged group.
FairShap: A Data Re-weighting Approach for Algorithmic Fairness based on Shapley Values
Algorithmic fairness is of utmost societal importance, yet the current trend in large-scale machine learning models requires training with massive datasets that are frequently biased.
DiffWire: Inductive Graph Rewiring via the Lovász Bound
Graph Neural Networks (GNNs) have been shown to achieve competitive results to tackle graph-related tasks, such as node and graph classification, link prediction and node and graph clustering in a variety of domains.
Ranked #1 on
Graph Classification
on IMDB-BINARY
